Towards Semantic Detection of Smells in Cloud Infrastructure Code.

Indika Kumara, Zoe Vasileiou, Georgios Meditskos, Damian A. Tamburri, Willem-Jan van den Heuvel, Anastasios Karakostas, Stefanos Vrochidis, Ioannis Kompatsiaris

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

11 Citaten (Scopus)


Automated deployment and management of Cloud applications relies on descriptions of their deployment topologies, often referred to as Infrastructure Code. As the complexity of applications and their deployment models increases, developers inadvertently introduce software smells to such code specifications, for instance, violations of good coding practices, modular structure, and more. This paper presents a knowledge-driven approach enabling developers to identify the aforementioned smells in deployment descriptions. We detect smells with SPARQL-based rules over pattern-based OWL 2 knowledge graphs capturing deployment models. We show the feasibility of our approach with a prototype and three case studies.

Originele taal-2Engels
TitelWIMS 2020: Proceedings of the 10th International Conference on Web Intelligence, Mining and Semantics
Aantal pagina's5
StatusGepubliceerd - 2020

Publicatie series

NaamPervasiveHealth: Pervasive Computing Technologies for Healthcare
ISSN van geprinte versie2153-1633

Bibliografische nota

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